Python 熊猫：根据多个条件生成句子，并在单独的列中显示它们

这是问题的后续行动 我有一个数据帧，如下所示：

           KPI              Tata      JSW    scope   BIC    Peer   BIC_diff  Avg_diff
0        Gross Margin %    0.5820    0.4760   Max    0.582  0.268        0    0.313 
2          SG&A/Revenue    0.1410    0.0300   Min    0.029  0.0645     0.112  0.0765
3                   ROA    0.0640    0.0930   Max    0.093  0.0457    -0.029  0.0183
4                   ROE    0.1380    0.2430   Max    0.243  0.1024    -0.105  0.0356
5    Inventory Turnover    2.2000    3.2700   Min    1.71   3.892      0.49  -1.692
6        Current Ratio     0.9000    0.8000   Min    0.5    1.15        0.4  -0.25

现在，我想添加另一列，其单元格值的条件为

df['scope']

，

df['BIC_diff']

和

df['Peer_diff']

。结果列如下所示。基本条件如下：

cond_comments = [(df['scope']=='Max') & (df['BIC_diff'] > 0) & (df['Avg_diff'] > 0),
             (df['scope']=='Max') & (df['BIC_diff'] <= 0) & (df['Avg_diff'] <= 0),
             (df['scope']=='Max') & (df['BIC_diff'] <= 0) & (df['Avg_diff'] > 0),
             (df['scope']=='Min') & (df['BIC_diff'] > 0) & (df['Avg_diff'] > 0),
             (df['scope']=='Min') & (df['BIC_diff'] <= 0) & (df['Avg_diff'] <= 0),
             (df['scope']=='Min') & (df['BIC_diff'] > 0) & (df['Avg_diff'] <= 0)]

为了实现上述目标，我尝试了以下方法：

cond_comments = [(df['scope']=='Max') & (df['BIC_diff'] > 0) & (df['Avg_diff'] > 0),
             (df['scope']=='Max') & (df['BIC_diff'] <= 0) & (df['Avg_diff'] <= 0),
             (df['scope']=='Max') & (df['BIC_diff'] <= 0) & (df['Avg_diff'] > 0),
             (df['scope']=='Min') & (df['BIC_diff'] > 0) & (df['Avg_diff'] > 0),
             (df['scope']=='Min') & (df['BIC_diff'] <= 0) & (df['Avg_diff'] <= 0),
             (df['scope']=='Min') & (df['BIC_diff'] > 0) & (df['Avg_diff'] <= 0)]
vals_comments = ['{0} is better than BIC and peer by {1} and {2} respectively'.format(df['KPI'],df['BIC_diff'],df['Avg_diff']),
             '{0} has scope of improvement by atleast {1}'.format(df['KPI'],df['Avg_diff']),
             'While {0} is better than its peer, still there is a scope of improvement by {1}'.format(df['KPI'],df['BIC_diff']),
             '{0} has scope of improvement by atleast {1}'.format(df['KPI'],df['Avg_diff']),
             '{0} is better than BIC and peer by {1} and {2} respectively'.format(df['KPI'],df['BIC_diff'],df['Avg_diff']),
             'While {0} is better than its peer, still there is a scope of improvement by {1}'.format(df['KPI'],df['BIC_diff'])]
df['Comments'] = pd.np.select(cond_comments, vals_comments,default='No Comment')

cond_comments=[（df['scope']='Max'）和（df['BIC_diff']>0）和（df['Avg_diff']>0），
（df['scope']='Max'）和（df['BIC_diff']0），
（df['scope']='Min'）&（df['BIC_diff']我将创建一个函数，首先执行所有条件，然后按行应用它。这样更容易添加新条件，并查看什么条件导致什么结果

def create_comment(line: dict) -> str:
    # column values are accessible as in a dictionary
    if (line['scope']=='Max') and (line['BIC_diff'] > 0) and (line['Avg_diff'] > 0):
        return '{0} is better than BIC and peer by {1} and {2} respectively'.format(line['KPI'],line['BIC_diff'],line['Avg_diff'])
    elif (line['scope']=='Max') and (line['BIC_diff'] <= 0) and (line['Avg_diff'] <= 0):
        return '{0} has scope of improvement by at least {1}'.format(line['KPI'],line['Avg_diff'])
    ### Insert the remaining conditions below
    else:
        return 'No Comment'

# Then apply with axis=1 to do it row-wise
df['Comments'] = df.apply(create_comment, axis=1)

def创建注释（行：dict）->str:
#列值可以像在字典中一样访问
如果（行['scope']=='Max'）和（行['BIC_diff']>0）以及（行['Avg_diff']>0）：
返回{0}比BIC和peer分别好{1}和{2}。格式（行['KPI']，行['BIC_diff']，行['Avg_diff']））
elif（line['scope']=='Max'）和（line['BIC_diff']在您的示例中没有
Avg_diff
列。这是打字错误！我已经纠正了这个问题。这很有用。尽管我做了一些修改。顺便说一句，我认为我们不需要声明
line:dict-->str
def create_comment(line: dict) -> str:
    # column values are accessible as in a dictionary
    if (line['scope']=='Max') and (line['BIC_diff'] > 0) and (line['Avg_diff'] > 0):
        return '{0} is better than BIC and peer by {1} and {2} respectively'.format(line['KPI'],line['BIC_diff'],line['Avg_diff'])
    elif (line['scope']=='Max') and (line['BIC_diff'] <= 0) and (line['Avg_diff'] <= 0):
        return '{0} has scope of improvement by at least {1}'.format(line['KPI'],line['Avg_diff'])
    ### Insert the remaining conditions below
    else:
        return 'No Comment'

# Then apply with axis=1 to do it row-wise
df['Comments'] = df.apply(create_comment, axis=1)